iterator

Iterators

Objects implementing __iter__ and __next__ — the protocol that powers every for loop in Python.

Files

File	Description
example.py	CountDown and BatchIterator classes

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Descriptive Example

Scenario

Build a custom countdown iterator and a batch iterator that yields chunks of 3 from a list.

class CountDown:
    def __init__(self, start):
        self.current = start

    def __iter__(self):
        return self

    def __next__(self):
        if self.current <= 0:
            raise StopIteration
        value = self.current
        self.current -= 1
        return value

for n in CountDown(5):
    print(n, end=" ")   # 5 4 3 2 1

What for actually does

for item in obj:
    ...

# equivalent to:
_iterator = iter(obj)       # calls obj.__iter__()
while True:
    try:
        item = next(_iterator)  # calls __next__()
    except StopIteration:
        break

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Interview Q&A

Q1: What is the difference between iterable and iterator?
A: An iterable has __iter__() returning an iterator (list, str, dict). An iterator has both __iter__() (returns self) and __next__().

Q2: Is a Python list an iterator?
A: No. A list is iterable. Each call to iter(my_list) creates a fresh iterator. Once exhausted, you need a new one.

Q3: What happens when __next__ has no more values?
A: It must raise StopIteration. The for loop catches this and exits normally.

Q4: Iterator vs generator?
A: Generators are a convenient way to create iterators using yield. Iterator classes use explicit __iter__/__next__.

Q5: Can you iterate a custom object?
A: Yes — implement __iter__ returning an object with __next__, or use a generator function with yield.

Q6: What is an iterator exhaustion bug?
A: Using the same iterator twice — second loop gets nothing because the iterator is already exhausted. Call iter() again for a fresh one.

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Run

python3 example.py